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The occurrence of acute hypotensive episode (AHE) in intensive care units can result in grave consequences and endanger the patient lives. How to detect and predict acute hypotensive episode in advance has become a clinical problem which is highly paid attention to by the medical world. In recent years, with the rapid development of the medical monitoring technology and signal analysis and processing methods, promoting a comprehensive study of forecasting approaches for acute hypotensive episode, the study mainly focuses on two aspects: one is the research of the vital signs that is likely related to the occurrence of acute hypotensive episode, showing that arterial blood pressure, heart rate and oxygen saturation , etc. can be acted as effective indicators. The other is to study the trend of changes in these vital signs, which would achieve forecasting acute hypotensive episode up to an hour in advance by defining a certain forecast window and the diagnostic threshold. It illustrates that integration of digitized signal processing technique with clinical monitoring parameters is the development direction for realizing intelligent monitoring technology. On the basis of continuing to enrich the database for monitoring, person concerned are committed to recognize the onset regularity of acute hypotension, looking for the approach that might forecast acute hypotensive episodes ahead of time and designing the intelligent forecast software. The study of this approach is beneficial to early prediction of acute hypotension and intervention, which would significantly reduce the death risk of patients and is of great value to clinical application.